Description: This report examines mortality and other actuarial assumptions for products sold at older ages.

Description: This research project studies the post level premium period lapse and mortality assumptions and experience for level premium term plans with a particular focus on the magnitude and impact of the “shock lapse” at the end of the level premium period.

Description: Studies company lapse and mortality experience at the end of the level premium period for term life plans, correlates the shock lapses with mortality deterioration and develops a regression model.

Description: Letter from the new chairman of the Technology Section Council introducing the new council members.

Description: This article discusses using Excel to calculate internal rate of return IRR and the potential complications associated with the task.

Description: Report on the Lapse and Mortality Experience of Post-Level Premium Period Term Plans

Description: The Product Development Section Council and the Committee on Life Insurance Research of the SOA engaged RGA Reinsurance Company to undertake a research project on level premium term life insurance products with a particular focus on the magnitude and impact of the 'shock lapse' at the end of the level premium period. Mortality was also studied. These are the Excel Pivot Tables for that study. Please see the SOA website experience studies for the full report.

Description: This article discusses a recently completed RGA in-depth study that looked at assumptions and experience for lapses and mortality at the end of the level premium period for level term business.

Description: Discusses Phase 1 survey results from the SOA/RGA post-level term research project.

Description: This actually is a copy of an appendix of a research paper sponsored by the SOA Committee on Finance Research. You can read the entire research paper: “Lapse Modeling for the Post-Level Period—a Practical Application of Predictive Modeling” at the SOA site https://www.soa.org/Research/Research-Projects/Finance-Investment/lapse-2015-modeling-post-level/#sthash.W9lERSls.dpbs, but you can read this valuable appendix copied here in this issue to see how to build a PM step-by-step using your data and the R programming language. We thank Richard Xu, Dihui Lai, Minyu Cao, Scott Rushing, and Tim Rozar for their excellent paper and the Society of Actuaries, for the permission to reprint this portion of the paper.